Control system engineering refers to a domain of engineering that deals with architectures, mechanisms and algorithms for maintaining output of a specific system or process within a desired range. Automated control systems are used extensively in industry and for example can be achieved using programmable logic controllers (PLC(s)), or in the case of more complex systems using distributed control systems (DCS) or supervisory control and data acquisition systems (SCADA).
Automated control systems rely on one or more controllers communicatively coupled to one or more field devices. Field devices (e.g. sensors, valves, switches, receivers and transmitters) are located within the process environment corresponding to the control system (for example, but not limited to, an industrial plant or system) and may be configured to perform physical or process control functions to control one or more components, processes or variables under observation within the process environment. Process controllers may be located within the process environment and are configured to receive signals from field devices, make control decisions, generate control signals and communicate with field devices.
Operation of control systems rely on a set of standard operating procedure(s) (SOP(s))—which prescribe one or more methods (i.e. sequence of steps and/or operator actions) for operating the control systems, and which one or more methods are considered optimal for achieving a desired process state or process outcome. Control systems operators are trained to implement standard operating procedures corresponding to the respective control systems processes that they are designated to operate.
Prior art systems implement various mechanisms to determine whether operators are complying with defined standard operating procedures—and to raise alerts or alarms in case of deviations from standard operating procedures. These prior art systems have been found to be disadvantageous as they operate on the assumptions that (i) a defined standard operating procedure is incapable of (or does not require) improvement and (ii) that any deviation from the defined standard operating procedure (including deviations which could potentially result in output or state optimization) is indicative of an error. These assumptions prevent operators from improving or optimizing existing standard operating procedures.
Additionally, with the passage of time and variations in plant conditions, there may be a need to deviate from a defined standard operating procedure to improve or maintain output conditions. There is accordingly a need for a solution that enables monitoring of operator compliance with defined standard operating procedures, and which further enables identification and adoption of improvements over an earlier defined standard operating procedure.